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Published in Findings of the Association for Computational Linguistics (EMNLP 2023) , 2023
This paper proposes a novel approach, IICOT, that leverages generative models, instruction learning, and chain-of-thoughts to enhance reasoning capabilities for implicit discourse relation recognition, achieving state-of-the-art performance on benchmark datasets.
Published in Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), 2024
This paper proposes a joint learning framework that combines prototypical learning, adversarial learning, and hub-migration based redistribution to enhance the performance of Pre-trained Language Models (PLMs) for Implicit Discourse Relation Recognition (IDRR).
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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